中国机器人在跳舞，美国机器人在发论文

远川科技评论02-26

炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！　　从去年春晚的转手绢，到今年春晚各路机器人联手登台，各大机器人主机厂轮番出圈。过去一年里，从走猫步到拳打创始人，再到机器人马拉松演唱会热舞都没落下，机器人的国民度更上一层楼，唯一遗憾是春节期间股票不开盘。　　相比群众基础渐深、看得见摸得着的中国机器人，美国机器人行业好像冷清很多。　　激进如特斯拉不惜停产Model S...

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\n　　从去年春晚的转手绢，到今年春晚各路机器人联手登台，各大机器人主机厂轮番出圈。过去一年里，从走猫步到拳打创始人，再到机器人马拉松演唱会热舞都没落下，机器人的国民度更上一层楼，唯一遗憾是春节期间股票不开盘。\n　　相比群众基础渐深、看得见摸得着的中国机器人，美国机器人行业好像冷清很多。\n　　激进如特斯拉不惜停产Model S/X服务机器人量产，目前口径也还是“2026年下半年开始交付”。沉寂多年的老网红波士顿动力勉强算另一个，在年初的CES上发布了一个脸上长着大型USB接口的机器人：\n\n　　波士顿动力的人形机器人Atlas\n　　美国的机器人确实很少，但机器人公司其实非常多。\n　　人工智能泰斗李飞飞初次创业就瞄准了机器人赛道，其公司World Labs主攻数据合成和机器人模型，OpenAI投资的Physical Intellence也是一家做模型的公司，创始团队就出自OpenAI和谷歌的DeepMind。\n　　英伟达自然也不会闲着，除了做芯片，还专为人形机器人设计了Isaac大模型平台，年内连更三次，比GPU还勤快。\n\n　　英伟达Issac平台为人形机器人提供模型训练和仿真测试\n　　可见中美产业界在机器人的发展前景上不乏共识，但科技树似乎点向了截然不同的方向：\n　　中国主攻硬件，机器人舞刀弄枪不在话下，有出息的已经在工厂拧螺丝了；美国主攻软件，虽然机器人没做出几个，但算法和论文发了不少，专利申请了一堆，产品发布会像是学术研讨会。\n　　前有Figure AI发布VLA模型带动公司估值大涨，后有特斯拉第三代机器人公开“端到端”视频学习取代传统编程，让硅谷的视线长久地停留在了公式和代码上。\n　　中国有强大的生产制造能力，美国有计算机科学深厚的产业基础，在机器人这个赛道上，双方似乎又要迎来一场赛跑。\n　　默契的分工\n　　两条分道扬镳的科技树，代表了人形机器人落地的两条腿：硬件和软件。\n　　有别于传统的工业机器人，人形机器人长远的目标是“通用性”，即机器人能像人一样，完成所有人类能做的事情。\n　　人类改造自然的工具都以人为基准设计，小到锅碗瓢盆的尺寸大到工厂产线的规划，即普罗泰戈拉所说“人是万物的尺度”。机器人想要做到“通用”，就得适应人类创造的事物，因此不但要做成人形，还要有人类一样灵活的四肢和灵巧的双手。\n　　同时，机器人无法感知真实世界的触感、重力、反馈，因此需要软件算法，让机器人理解真实世界的物理学规则。举例来说，当机器人拿起一个鸡蛋，硬件部分负责执行这个动作，软件决定机器人施加多大的力，不至于把鸡蛋捏爆。\n　　也就是说，硬件是机器人的肉身，软件是机器人的大脑，两者缺一不可，既可以共同进步，也可以互为绊脚石。\n　　对中国主机厂来说，机器人跳舞不是纯粹的传播诉求，而是各种意义上的秀肌肉，向产业界展示自己在硬件上下了多少功夫。\n　　机器人是个全新的产业，与现有产业的零部件通用程度不高。比如覆盖在机器人外表的“电子皮肤”，需要实现类似人类皮肤对外界的感知力，对传感器的灵敏度和精确度的要求远超行业标准，还要兼顾重量、成本，尚未形成统一的解决方案。\n　　又比如硬件价值占比最高的关节。就像人类关节支撑四肢活动，机器人的关节是完成一切复杂操作的基础，髋关节的强度决定了能搬运多重的货物，拇指、食指的指尖关节决定了能穿多细的针、引多细的线。\n　　就连走路时更自然的步态、热舞时更灵活的扭胯，都由关节方案的先进性决定。\n\n　　特斯拉展示的人形机器人的膝盖关节\n　　相比之下，美国机器人公司的重心集中在软件环节，致力于越过大语言模型与空间智能的分水岭：对物理规则的理解。\n　　举例来说，语言模型也知道苹果会掉到地上，因为它在训练过程中输入过无数个苹果会掉在地上的数据，但这是对物理现象的一种描述，而不是理解物理规则本身。\n　　语言模型类似一种概率预测，推测下一个词是什么，但空间智能更接近真实物理世界的模拟，算法需要判断下一秒周围环境的变化。相比舞刀弄枪，拧瓶盖、开罐头，反而是更难攻克的场景。\n　　无论是谷歌和英伟达这类大公司，还是World Labs和Physical Intellence这些初创公司，瞄准的都是软件层面的世界模型，让AI学会物理学这门必修课。\n　　中国在给机器人重塑金身，美国在给机器人训练大脑，这样一硬一软的默契分工，似乎总让人似曾相识。\n　　没错，就是新能源车产业。\n　　长了腿的电动车\n　　电动车——确切的说是自动驾驶，可以视为人形机器人的“前置产业”。如果电动车是长了轮子的机器人，那么人形机器人就是长了腿的电动车。\n　　自动驾驶与人形机器人的主体架构都可以看作“AI大脑+执行器”：两者都依靠各类摄像头、传感器获取外界数据，通过算力芯片和模型算法进行决策，再通过电机驱动车身或机体执行任务。\n　　区别在于，人形机器人需要获取的数据更精确（更多类型传感器和更高的精度），需要处理的决策更复杂（通用大模型），执行的任务更多样（更灵活的关节和更科学的工学设计）。\n　　对比两者的关键零部件，大多都在技术上同根同源，只是在规格和参数上有差异。\n　　人形机器人的关节本身就是微缩版高性能电机；特斯拉Optimus胸前的2.3kWh的电池组，电路保护和能量管理系统都复用了电动车的电池包技术；还有用来控制电动车车轮转速的电控技术，机器人要手持鸡蛋不碎，靠的就是这个。\n　　硬件高度通用，软件更是拿来就用。对机器人来说，在工厂里识别一个螺栓和在路上辨别红绿灯用的算法都是类似的，Optimus甚至照搬电动车用的FSD算法。\n\n　　Optimus照搬特斯拉的FSD模型\n　　这也是为什么在电动车上有所建树的公司，都动过机器人的心思。特斯拉自然不必多说，小鹏的机器人也已经造出来了，理想也表示自己要All in AI，转型具身智能公司。\n　　中美两国一硬一软的默契分工，在供应链上体现的更加明显。中国是脱胎汽车产业的制造业企业，美国则是成片的软件和芯片设计公司。\n　　中国的机器人供应链，最忙的都是车圈的老熟人。例如被多方爆料拿下Optimus关节订单的三花智控，就是特斯拉电动车热管理模块的供应商。传闻中拿到订单的，还包括特斯拉底盘供应商、Model 3/Y铝合金压铸件供应商。\n　　汽车Tier1均胜电子则直接官宣升级为“汽车+机器人双轨Tier 1”，凭借过去在电动车电池管理、底盘控制等积攒的综合实力，开始给人形机器人核心零部件供货，客户除了传言中的特斯拉，还有宇树、智元等中国主机厂。\n　　人形机器人这两年体操跳得越来越好，很难说没有这些汽车供应商的功劳。\n　　硬件有中国供应链送温暖，软件自然有美国巨头跨界驰援。\n　　英伟达不必多说，霸占高算力芯片市场多年，专门为机器人准备了算力芯片Jetson Thor——其实就是自动驾驶芯片Drive Thor的“机器人版本”，不仅用的同样的芯片架构（Blackwell），连最高算力都差不多。\n　　美国自动驾驶的全村希望Waymo，同样是机器人积极分子，不仅兄弟公司DeepMind联手推出机器人世界模型，还将其激光雷达和摄像头技术，移植到了谷歌的RT-2机器人实验平台，谷歌自己则在去年发布了用于机器人的Gemini Robotics模型。\n　　上一个利用中国强大的生产制造能力与美国雄厚的计算机产业获得成功的公司，恰恰是正在为机器人摇旗呐喊的特斯拉。\n　　作为特斯拉第一座海外工厂，上海工厂2019年1月开工，12月交付，创造了“当年开工，当年竣工，当年生产，当年交付”的奇迹，背靠长三角发达的汽车产业链，挽救了刚刚走出产能地狱的特斯拉。\n　　目前，上海工厂依然是特斯拉产能最猛的工厂，不仅支撑着特斯拉在中国的交付，也肩负着海外市场的出口任务。\n　　但与此同时，FSD算法的研发、AI5/AI6芯片的设计方案、xAI的大模型和数据中心等一切与软件有关的部门，都不约而同的放在了美国大本营。\n\n　　位于孟菲斯的xAI数据中心\n　　如今，相似的产业背景、相似的默契分工，好像正在机器人产业重新上演。\n　　没有下一个特斯拉\n　　顶尖的人才总是会向产业的高地流动，美国是计算机科学产业的发源地，优势从集成电路一路领先到了人工智能，在软件、互联网、芯片设计等细分市场，金字塔尖林立的巨头几乎都是美国公司。\n　　这些产业不仅吸引着全球最顶级的人才，也在为前沿技术不断培养着人才预备役。特斯拉崛起的核心因素之一，是微软、谷歌、英伟达这些IT巨头源源不断的人才输送，他们虽然是制造业的门外汉，但在软件领域一骑绝尘。\n　　中国的优势自然是制造业，很多老产业都是新兴市场的“前置产业”。新能源车的动力电池出现前，消费电子产品的锂电池就早早在东亚地区落地生根。这个过程中，电化学人才跟随产业链的转移流动，为动力电池的提供了可观的人才储备。\n　　在机器人领域，广袤的制造业一直在源源不断输送弹药。美国产业界自然深知这一点，硅谷风投公司a16z在一份名为《America Cannot Lose the Robotics Race》的报告里说[6]：\n　　“中国企业注定会主导并垄断一个又一个细分市场，直至所有竞争对手的生产都变得无利可图。”\n　　根据大摩此前爆料，特斯拉Optimus能打到20000美元左右，中国的低成本零部件功不可没[4]。而TrendForce分析师透露，中国零部件厂商向特斯拉供货后，会根据测试反馈进行改进，然后将改进后的版本提供给国内制造商[5]。\n　　基于这种产业特征，美国的高科技公司无一例外都用软件构筑核心附加值，把生产制造交给庞大的中国供应链，自己则牢牢掌握价值量最高、也是美国绝对的产业优势环节：软件。\n　　作为供应链大师，库克接过乔布斯的遗产，在中国建立起严丝合缝的供应链帝国。以不到20%的手机出货量份额，拿走行业超过80%的营业利润[3]。上海工厂负担特斯拉超过半数的交付量，同时，一座座数据中心在美国的拔地而起。\n　　2023年，谷歌关闭了机器人硬件研发部门Everyday Robots，将其技术资产并入DeepMind，基本放弃了机器人硬件开发，全面转向以算法为核心的机器人“大脑”的研发。\n　　从消费电子（苹果）、新能源车（特斯拉）到机器人（谷歌），把资源投入软件环节，既是基于自身优势产业的务实选择，也是获取高利润率和高附加值的关键。\n　　但在软件环节，中国产业界也没闲着。\n　　智能手机时代，中美在操作系统、芯片设计等环节存在巨大差距，导致核心零部件受制于人。但在新能源车产业，中美企业的自动驾驶能力孰强孰弱也许见仁见智，但双方的差距明显小了很多。\n　　原因在于，中国发达的互联网产业为自动驾驶、人工智能等新兴领域贡献了充足的人才储备，美国科技公司在软件上的统治力逐渐松动。去年Deepseek让美国产学界集体破防，今年字节Seedance2.0发布，老外集体被+86手机号卡在注册环节，就是典型的例证。\n　　具体到人形机器人“大脑”，在主流技术路线上，双方的差距在快速弥合。\n　　例如当前最被看好的VLA技术路线，最早由谷歌在2023年7月首创（RT-2）、OpenAI次年5月跟进（GPT-4o）。到了2025年，智元机器人ViLLA和小鹏VLA 2.0就前后脚落地了，一个能利用人类视频学习，一个取消了“语言转译”的中间环节，已经做出了差异化的改进。\n　　当下特斯拉被中国车企轮番包抄的现实，未来也可能会在人形机器人上重新上演。\n　　作为美国制造业的大恩人，既干过软件，又下过产线的马斯克显然有清醒的认知。去年初的财报电话会上，马斯克给各家厂商的人形机器人排了个名次：\n　　特斯拉的Optimus自然毫无悬念位列第一，但第二到第十，“我担心全都是中国公司[8]。”\n新浪声明：此消息系转载自新浪合作媒体，新浪网登载此文出于传递更多信息之目的，并不意味着赞同其观点或证实其描述。文章内容仅供参考，不构成投资建议。投资者据此操作，风险自担。\n\n\n海量资讯、精准解读，尽在新浪财经APP\n\n责任编辑：何俊熹","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":1,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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